If you study recent technological developments that have taken the world by storm, the most common names you would come across are Artificial Intelligence (AI), Machine Learning and Deep Learning.
These are not just any words or sci-fi concepts that novelists and movie producers previously explored. These three aspects have now found use in today’s world and have truly changed the scope of life.
If your child is now at a crossroads and is wondering which career to choose that will have the maximum job opportunities for students, you can always suggest choosing anyone from AI, Machine Learning and Deep Learning. All three aspects have plenty of future job opportunities with high-paying salaries.
However, our main focus will be to explain the fuss about Machine Learning and Deep Learning, followed by explaining which career has more scope in the future and other aspects related to learning and job opportunities.
Machine Learning is a sophisticated branch of AI that deals with data analytics and analytical model building. It is a general idea that the system can learn something from the data by identifying the patterns and then make a decision.
This decision does not involve any human, and it is made with minimal human intervention. Computer experts got this idea because of their curiosity as they wanted to see whether computers could learn only from the data.
Once students understand the significance of Machine Learning, they become more curious and start exploring more about the career opportunities in machine learning.
Deep Learning is a part of machine learning that computers do that comes very naturally to humans, i.e., learn by example. Deep Learning is a technology used in most driverless cars that enable the machine to stop at a sign, differentiate between pedestrians and a lamppost.
The voice commands you give on your smartphone, tablets, TVs and Bluetooth speakers all work on the principle of Deep Learning. In recent years it is achieving many results that were earlier considered impossible.
The main prospect of Deep Learning is its accuracy. With its state-of-the-art appliances, it can exceed human-level performance within no time. These machines are trained by huge quantities of labeled data and network architectures that themselves have numerous layers.
As a newbie, you can easily get confused between Machine Learning and Deep Learning. Hence, today we will uncover some of the basic similarities and differences between the two.
● Machine Learning is all about using the data, learning from it and making informed decisions about what the machine just learned. Machine Learning trains on the CPU, taking less time to train. The output of Machine Learning is the numerical form for categorisation and arranging applications. The main issue is that Machine Learning has restricted tuning capabilities.
● Deep Learning creates a neural network architecture that learns by itself and then takes a decision. Deep Learning trains on GPU and takes more time than Machine Learning. The output is free from free elements like words and noises. With Deep Learning, the apparatus can be tuned in a couple of ways.
When these two tech giants are compared, there is no straight answer for which is better or worse.
Both have their shares of similarities and differences, but what matters the most is the student's interest. Whether the student chooses to learn Machine Learning or Deep Learning will decide which aspect they will love the most.
Machine Learning has numerous excellent career opportunities for students. The scope of machine learning is not restricted to a certain field. Instead, it is spread across banking, finance, media, robotics, IT, automobiles, gaming, etc.
Since it can be accessed in all domains, the experts are working on revolutionizing the world for the future. Several schools and educational institutes promote Machine Learning and encourage students to learn about Machine Learning’s future scope.
In the current scenario, an average working professional expert in Machine Learning will earn a salary of up to ₹728,724 per annum. With an experience of 6-14 years, it can go up to ₹19,30,000. LinkedIn community experts quoted this amount.
Deep Learning helps improve the accuracy of predictions and enables the users to get improved data-driven decisions. Over the next few years, it is predicted that Deep Learning could prove to be very useful in performing common AI tasks like image recognition.
Students who are keen on learning about automation and how slowly AI can be used to replace human interaction would benefit the most by studying Deep Learning. Since it deals with neural networks architecture, the chances of booking in the next few years are very high.
It can be assured that Deep Learning has a promising future because Google has acquired DeepMind Technologies, which holds the most promises for global marketers. With the current pace at which Deep Learning is progressing, developers will soon be forced to learn more about it to survive the competition.
Engineers with more than eight years of experience can earn an average salary of ₹7-12 LPA. If you’re a professional and have experience of more than 15 years, you can easily earn around ₹25-48 LPA.
If your child is curious about learning more about AI, Machine Learning or Deep Learning, you should encourage them and choose their path. All three are great career choices and can help your child secure a stable future.
This was an all-an-out basis of Machine Learning and Deep Learning. We have covered the basics, what it is and explained the job opportunities and future scope for students.
Students can now make an informed decision about Machine Learning as an exciting career choice as per the aspects mentioned in this blog. In our GIIS Ahmedabad, we also encourage students to learn what they like, helping them prosper and decide about their careers.
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A highly motivated and dedicated educator with nearly 24 years of teaching experience, Ms. Deepika Sodhi is the Academic Supervisor for International Curricula at Global Indian International School (GIIS) SMART Campus, Singapore.
Ms. Sodhi has a rich experience of teaching Physics across curricula such as the IB, Cambridge IGCSE and CBSE. She has served as an Exam Officer for Cambridge Assessment International Education. Currently, she is an IB Assessment Officer, and a member of International Schools Network and International Baccalaureate Educator Network.
In her free time, Ms. Sodhi enjoys writing blogs, creating guiding material for training staff and community service.